Instructions to use saik0s/comfy_backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use saik0s/comfy_backup with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="saik0s/comfy_backup", filename="ComfyUI/models/text_encoders/gemma-3-12b-it-q2_k.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use saik0s/comfy_backup with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: llama cli -hf saik0s/comfy_backup:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: llama cli -hf saik0s/comfy_backup:Q4_K_S
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf saik0s/comfy_backup:Q4_K_S
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf saik0s/comfy_backup:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf saik0s/comfy_backup:Q4_K_S
Use Docker
docker model run hf.co/saik0s/comfy_backup:Q4_K_S
- LM Studio
- Jan
- Ollama
How to use saik0s/comfy_backup with Ollama:
ollama run hf.co/saik0s/comfy_backup:Q4_K_S
- Unsloth Studio
How to use saik0s/comfy_backup with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for saik0s/comfy_backup to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for saik0s/comfy_backup to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for saik0s/comfy_backup to start chatting
- Pi
How to use saik0s/comfy_backup with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf saik0s/comfy_backup:Q4_K_S
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "saik0s/comfy_backup:Q4_K_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use saik0s/comfy_backup with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf saik0s/comfy_backup:Q4_K_S
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default saik0s/comfy_backup:Q4_K_S
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use saik0s/comfy_backup with Docker Model Runner:
docker model run hf.co/saik0s/comfy_backup:Q4_K_S
- Lemonade
How to use saik0s/comfy_backup with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull saik0s/comfy_backup:Q4_K_S
Run and chat with the model
lemonade run user.comfy_backup-Q4_K_S
List all available models
lemonade list
| from comfy_api.latest._io import Combo, MultiCombo | |
| def test_multicombo_serializes_multi_select_as_object(): | |
| multi_combo = MultiCombo.Input( | |
| id="providers", | |
| options=["a", "b", "c"], | |
| default=["a"], | |
| ) | |
| serialized = multi_combo.as_dict() | |
| assert serialized["multiselect"] is True | |
| assert "multi_select" in serialized | |
| assert serialized["multi_select"] == {} | |
| def test_multicombo_serializes_multi_select_with_placeholder_and_chip(): | |
| multi_combo = MultiCombo.Input( | |
| id="providers", | |
| options=["a", "b", "c"], | |
| default=["a"], | |
| placeholder="Select providers", | |
| chip=True, | |
| ) | |
| serialized = multi_combo.as_dict() | |
| assert serialized["multiselect"] is True | |
| assert serialized["multi_select"] == { | |
| "placeholder": "Select providers", | |
| "chip": True, | |
| } | |
| def test_combo_does_not_serialize_multiselect(): | |
| """Regular Combo should not have multiselect in its serialized output.""" | |
| combo = Combo.Input( | |
| id="choice", | |
| options=["a", "b", "c"], | |
| ) | |
| serialized = combo.as_dict() | |
| # Combo sets multiselect=False, but prune_dict keeps False (not None), | |
| # so it should be present but False | |
| assert serialized.get("multiselect") is False | |
| assert "multi_select" not in serialized | |
| def _validate_combo_values(val, combo_options, is_multiselect): | |
| """Reproduce the validation logic from execution.py for testing.""" | |
| if is_multiselect and isinstance(val, list): | |
| return [v for v in val if v not in combo_options] | |
| else: | |
| return [val] if val not in combo_options else [] | |
| def test_multicombo_validation_accepts_valid_list(): | |
| options = ["a", "b", "c"] | |
| assert _validate_combo_values(["a", "b"], options, True) == [] | |
| def test_multicombo_validation_rejects_invalid_values(): | |
| options = ["a", "b", "c"] | |
| assert _validate_combo_values(["a", "x"], options, True) == ["x"] | |
| def test_multicombo_validation_accepts_empty_list(): | |
| options = ["a", "b", "c"] | |
| assert _validate_combo_values([], options, True) == [] | |
| def test_combo_validation_rejects_list_even_with_valid_items(): | |
| """A regular Combo should not accept a list value.""" | |
| options = ["a", "b", "c"] | |
| invalid = _validate_combo_values(["a", "b"], options, False) | |
| assert len(invalid) > 0 | |